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Enhancing undergraduate students' sensing and data-informed decision-making through a smart cities project

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Conference

2022 ASEE Annual Conference & Exposition

Location

Minneapolis, MN

Publication Date

August 23, 2022

Start Date

June 26, 2022

End Date

June 29, 2022

Conference Session

Environmental Engineering Division Technical Session 3

Page Count

13

Permanent URL

https://peer.asee.org/41875

Download Count

77

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Paper Authors

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Joe Moore Carnegie Mellon University

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Cheyu Lin Carnegie Mellon University

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A Ph.D. student majors in Civil and Environmental Engineering at Carnegie Mellon University.

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Katherine Flanigan Carnegie Mellon University

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Abstract

Smart cities promise the ability to use data to inform city planning, resource allocation, and so much more. To do so, they require capturing, processing, and interpreting data. Considerable design work is required to ensure that data captured within smart cities can actually be used to inform decisions. For smart cities and the sensed infrastructure they comprise to be as widely adopted, as current interest suggests they will be, future engineers will need to be familiar with both the design and data aspects of smart cities. Today’s engineering students will be those future engineers. Our junior-level Civil and Environmental Engineering (CEE) project course has typically included a project involving sensing and data analysis. This year, for the first time, we deployed a project that used smart cities as the context for a project requiring full-scale design, sensing, data analysis, and decision-making amid uncertainty. Importantly, while many smart cities technologies are privacy invasive, our project was done using technology that is not privacy invasive. We assessed whether the project achieved the content and skill-oriented objectives by surveying students quantitatively and qualitatively. Our quantitative and qualitative data suggest that students achieved many of these objectives. Notably, student perception data suggest increases in: their appreciation for coding, sensing, and data analysis for CEE; their ability to integrate sensing and data-informed decision making; and their understanding of the potential impact of smart cities. The qualitative student comments align with our quantitative data. Smart cities provide much promise for future urban environments. To capitalize on those promises, engineers will have to gain new competencies in design, sensing, and data-informed decision making. Our junior-level smart cities project offers some ideas for how to get there.

Moore, J., & Lin, C., & Flanigan, K. (2022, August), Enhancing undergraduate students' sensing and data-informed decision-making through a smart cities project Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. https://peer.asee.org/41875

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